Deep neural networks (DNNs) are among the most powerful machine learning tools used for natural language processing [1]}, image classification [2]}, sound recognition [3]}, and more. DNNs are powerful because of their free input and output forms, which other methods lack [4]}. This advantage can be applied to real-world time-series data problems, such as nowcasting (NC), which uses a DNN to predict the next time step for power system monitoring [5]}, rainfall prediction [6]}, cutting-force prediction, and other problems.
